Language Technology, 6 credits

Språkteknologi, 6 hp

TDP030

Course starting semester

Main field of study

Programming

Course level

First cycle

Course type

Programme course

Examiner

Marco Kuhlmann

Director of studies or equivalent

Jalal Maleki

Education components

Preliminary scheduled hours: 48 h
Recommended self-study hours: 112 h

Available for exchange students

Yes

Possible deviation from course syllabus/programme syllabus

ECV = Elective / Compulsory / Voluntary

Course offered for		Semester	Period	Timetable module	Language	Campus	ECV
6KIPR	Programming	6 (Spring 2018)	1	2	Swedish/English	Linköping, Valla	E

Main field of study

Programming

Course level

First cycle

Advancement level

G2X

Course offered for

Programming

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

discrete mathematics
programming

Previous courses in machine learning are useful but no requirement for the course.

Intended learning outcomes

Language technology is technology for the analysis and interpretation of natural language, a key component of smart search engines, personal digital assistants, and many other innovative applications. The goal of this course is to give an introduction to language technology as an application area, as well as to its basic methods. The course focuses on methods that process text.

On completion of the course, the student should be able to:

explain basic methods for the analysis and interpretation of words, sentences, and texts
practically apply language technology methods and systems to texts and text collections
evaluate language technology components and systems using standard validation methods
judge the difficulty and the feasibility of language technology applications

Course content

basic methods and techniques for the analysis and interpretation of words, sentences, and texts, such as text segmentation, part-of-speech tagging, syntactic analysis, semantic analysis, and text classification
language technology systems, such as information extraction systems and question answering systems
validation methods
tools, software libraries, and data

Teaching and working methods

The course is given in the form of lectures, lab sessions, and supervision in connection with a minor project.

Examination

UPG1	Project assignments	2 credits	U, 3, 4, 5
LAB1	Practical assignments	2 credits	U, 3, 4, 5
TEN1	Written examination	2 credits	U, 3, 4, 5
KTR1	Optional written tests	0 credits	U, G

The optional written tests give bonus points for the first attempt at the written examination. The final grade for the course is the median of the grades awarded for LAB1, TEN1, and UPG1.

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för datavetenskap

Director of Studies or equivalent

Jalal Maleki

Examiner

Marco Kuhlmann

Course website and other links

http://www.ida.liu.se/~TDP030/

Education components

Preliminary scheduled hours: 48 h
Recommended self-study hours: 112 h

Course literature

Kurskompendium som tillhandahålls av institutionen. / Lecture notes provided by the department.

Code	Name	Scope	Grading scale
UPG1	Project assignments	2 credits	U, 3, 4, 5
LAB1	Practical assignments	2 credits	U, 3, 4, 5
TEN1	Written examination	2 credits	U, 3, 4, 5
KTR1	Optional written tests	0 credits	U, G

The optional written tests give bonus points for the first attempt at the written examination. The final grade for the course is the median of the grades awarded for LAB1, TEN1, and UPG1.

Student rights and obligations (login required)
Linköping University common rules and regulations (in Swedish)

Kurskompendium som tillhandahålls av institutionen. / Lecture notes provided by the department.

Download

Download course literature list as PDF

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize

		I	U	A	Modules
1. DISCIPLINARY KNOWLEDGE AND REASONING
	1.1 Knowledge of underlying mathematics and science (G1X level)			X
	1.2 Fundamental engineering knowledge (G1X level)			X
	1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)		X		TEN1
	1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)
	1.5 Insight into current research and development work
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
	2.1 Analytical reasoning and problem solving		X		LAB1 UPG1
	2.2 Experimentation, investigation, and knowledge discovery		X		LAB1 UPG1
	2.3 System thinking
	2.4 Attitudes, thought, and learning		X		UPG1
	2.5 Ethics, equity, and other responsibilities
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
	3.1 Teamwork			X	LAB1 UPG1
	3.2 Communications			X	UPG1
	3.3 Communication in foreign languages			X
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
	4.1 External, societal, and environmental context	X
	4.2 Enterprise and business context
	4.3 Conceiving, system engineering and management
	4.4 Designing
	4.5 Implementing
	4.6 Operating
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
	5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development
	5.2 Economic conditions for knowledge development
	5.3 Identification of needs, structuring and planning of research or development projects
	5.4 Execution of research or development projects
	5.5 Presentation and evaluation of research or development projects

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